Vibration-based gait analysis via instrumented buildings. (October 2019)

• Record Type: Journal Article
• Authors: Kessler, Ellis; Malladi, Vijaya VN Sriram; Tarazaga, Pablo A
• Is Part Of: International journal of distributed sensor networks. Volume 15:Number 10(2019)
• Publication Date: 2019-10
• Subjects: Floor vibrations -- stride length -- swing time -- step size -- smart infrastructure -- human gait; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147719881608
• Languages: English
• ISSNs: 1550-1329

Abstract

Gait analysis is an invaluable tool in diagnosing and monitoring human health. Current techniques often rely on specialists or expensive gait measurement systems. There is a clear space in the field for a simple, inexpensive, quantitative way to measure various gait parameters. This study investigates if useful quantitative gait parameters can be extracted from floor acceleration measurements produced by the input of foot falls. A total of 17 participants walked along a 115-ft-long hallway while underfloor mounted accelerometers measured the vertical acceleration of the floor. Signal-energy-based algorithms detect the heel strike of each step during trials. From the detected footsteps, gait parameters such as the average stride length, the time between steps, and the step signal energy were calculated. In this study, a single accelerometer was shown to be enough to detect steps over a 115-ft corridor. Distributions for all gait parameters measured were generated for each participant, showing a normal distribution with low standard deviation. The success of gait analysis using underfloor accelerometers presents possibilities in the widespread adaptation of gait measurements. The ease of installation and operation offers an opportunity to gather long-term gait measurements. Such data will augment current gait diagnostic approaches by filling the gaps between specialist visits.